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Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm

Modal-free optimization algorithms do not require specific mathematical models, and they, along with their other benefits, have great application potential in adaptive optics. In this study, two different algorithms, the single-dimensional perturbation descent algorithm (SDPD) and the second-order s...

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Autores principales: Chen, Bo, Zhou, Yilin, Li, Zhaoyi, Jia, Jingjing, Zhang, Yirui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181763/
https://www.ncbi.nlm.nih.gov/pubmed/37177573
http://dx.doi.org/10.3390/s23094371
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author Chen, Bo
Zhou, Yilin
Li, Zhaoyi
Jia, Jingjing
Zhang, Yirui
author_facet Chen, Bo
Zhou, Yilin
Li, Zhaoyi
Jia, Jingjing
Zhang, Yirui
author_sort Chen, Bo
collection PubMed
description Modal-free optimization algorithms do not require specific mathematical models, and they, along with their other benefits, have great application potential in adaptive optics. In this study, two different algorithms, the single-dimensional perturbation descent algorithm (SDPD) and the second-order stochastic parallel gradient descent algorithm (2SPGD), are proposed for wavefront sensorless adaptive optics, and a theoretical analysis of the algorithms’ convergence rates is presented. The results demonstrate that the single-dimensional perturbation descent algorithm outperforms the stochastic parallel gradient descent (SPGD) and 2SPGD algorithms in terms of convergence speed. Then, a 32-unit deformable mirror is constructed as the wavefront corrector, and the SPGD, single-dimensional perturbation descent, and 2SPSA algorithms are used in an adaptive optics numerical simulation model of the wavefront controller. Similarly, a 39-unit deformable mirror is constructed as the wavefront controller, and the SPGD and single-dimensional perturbation descent algorithms are used in an adaptive optics experimental verification device of the wavefront controller. The outcomes demonstrate that the convergence speed of the algorithm developed in this paper is more than twice as fast as that of the SPGD and 2SPGD algorithms, and the convergence accuracy of the algorithm is 4% better than that of the SPGD algorithm.
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spelling pubmed-101817632023-05-13 Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm Chen, Bo Zhou, Yilin Li, Zhaoyi Jia, Jingjing Zhang, Yirui Sensors (Basel) Communication Modal-free optimization algorithms do not require specific mathematical models, and they, along with their other benefits, have great application potential in adaptive optics. In this study, two different algorithms, the single-dimensional perturbation descent algorithm (SDPD) and the second-order stochastic parallel gradient descent algorithm (2SPGD), are proposed for wavefront sensorless adaptive optics, and a theoretical analysis of the algorithms’ convergence rates is presented. The results demonstrate that the single-dimensional perturbation descent algorithm outperforms the stochastic parallel gradient descent (SPGD) and 2SPGD algorithms in terms of convergence speed. Then, a 32-unit deformable mirror is constructed as the wavefront corrector, and the SPGD, single-dimensional perturbation descent, and 2SPSA algorithms are used in an adaptive optics numerical simulation model of the wavefront controller. Similarly, a 39-unit deformable mirror is constructed as the wavefront controller, and the SPGD and single-dimensional perturbation descent algorithms are used in an adaptive optics experimental verification device of the wavefront controller. The outcomes demonstrate that the convergence speed of the algorithm developed in this paper is more than twice as fast as that of the SPGD and 2SPGD algorithms, and the convergence accuracy of the algorithm is 4% better than that of the SPGD algorithm. MDPI 2023-04-28 /pmc/articles/PMC10181763/ /pubmed/37177573 http://dx.doi.org/10.3390/s23094371 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Chen, Bo
Zhou, Yilin
Li, Zhaoyi
Jia, Jingjing
Zhang, Yirui
Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title_full Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title_fullStr Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title_full_unstemmed Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title_short Adaptive Optical Closed-Loop Control Based on the Single-Dimensional Perturbation Descent Algorithm
title_sort adaptive optical closed-loop control based on the single-dimensional perturbation descent algorithm
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181763/
https://www.ncbi.nlm.nih.gov/pubmed/37177573
http://dx.doi.org/10.3390/s23094371
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